Functional Use of Eye Movements for an Acting System

Brouwer, Anouk J. de; Flanagan, J. Randall; Spering, Miriam

doi:10.1016/j.tics.2020.12.006

Cited by 56 publications

(45 citation statements)

References 103 publications

(120 reference statements)

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“…Other interception studies using non-reaction time paradigms have also shown that based on object speed, participants use different strategies that involve initiating a manual response when either the time-to-collision or distance between the projectile and the body crosses a certain threshold Port et al 1997;Rushton and Wann 1999;Zago et al 2004). One of the most prominent hypotheses generated from the interception studies is that during tracking movements, an efference copies of oculomotor commands associated with the smooth pursuit eye movement that track projectiles serve as feedforward input to guide limb movements (reviewed in Ilg 2008;de Brouwer et al 2021). But movement kinematics and response times are only one aspect of the interception problem, real-world catching movements also require posture stabilization to absorb the kinetic energy of the projectile.…”

Section: Signal-dependent Noise Associated With Visual Tracking Might Influence Timing Of Motor Responsesmentioning

confidence: 99%

“…Though we did not record eye movements in this study, participants likely tracked the moving objects with smooth pursuit eye movements (SPEM) with high gains (Mrotek and Soechting 2007). The nervous system may have used efferent copies of the oculomotor commands associated with SPEM as inputs to set gains of feedforward and feedback motor responses (de Brouwer et al 2021). It has been hypothesized that signal-dependent noise contaminates SPEM and causes larger fluctuations in the recorded gaze signals at higher SPEM velocities (Medina and Lisberger 2007;Joshua and Lisberger 2014).…”

Section: Signal-dependent Noise Associated With Visual Tracking Might Influence Timing Of Motor Responsesmentioning

confidence: 99%

“…A key prediction from this hypothesis is that the amplitude of the feedforward motor response would scale with target momentum, regardless of whether the momentum increased due to speed or mass. We also hypothesized that motor responses are timed based on a model-free online motion-processing system (La Scaleia et al 2015) that likely uses an efference copy of smooth pursuit eye movements as a feedforward input to guide interceptive hand movements (reviewed in Ilg 2008;de Brouwer et al 2021). The naïve prediction from this hypothesis is that faster target velocities will initiate early motor responses.…”

Section: Introductionmentioning

confidence: 99%

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Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: A preliminary study

Kurtzer

Singh

2021

Preprint

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An important window into sensorimotor function is how we catch moving objects. Studies that examined catching of free-falling objects report that the timing of the motor response is independent of the momentum of the projectile, whereas the motor response amplitude scales with projectile momentum. However, this pattern may not be a general strategy of catching since objects accelerate under gravity in a characteristic manner (unlike object motion in the horizontal plane) and the human visual motion-processing system is not adept at encoding acceleration. Accordingly, we developed a new experimental paradigm using a robotic manipulandum and augmented reality where participants stabilized against the impact of a virtual object moving at constant velocity in the horizontal plane. Participants needed to apply an impulse that mirrored the object momentum to bring it to rest and received explicit feedback on their performance. In different blocks, object momentum was varied by an increase in its speed or mass. In contrast to previous reports on free falling objects, we observed that increasing object speed caused earlier onset of arm muscle activity and limb force relative to the impending time to contact. Also, arm force increased as a function of target momentum linked to changes in speed or mass. Our results demonstrate velocity-dependent timing to catch objects and a complex pattern of scaling to momentum.

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Section: Signal-dependent Noise Associated With Visual Tracking Might Influence Timing Of Motor Responsesmentioning

confidence: 99%

Section: Signal-dependent Noise Associated With Visual Tracking Might Influence Timing Of Motor Responsesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: A preliminary study

Kurtzer

Singh

2021

Preprint

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“…This tight spatial and temporal coupling of the eye and hand movement is the hallmark of coordination [ 3 ]. However, despite such behavioral coupling, distinct neural pathways are thought to control the initiation and stopping of these effectors [ 4 , 5 ]. The neural pathways involved in generating eye and hand movements are thought to diverge in the parietal cortex after common early processing in visual areas.…”

Section: Introductionmentioning

confidence: 99%

Computational Mechanisms Mediating Inhibitory Control of Coordinated Eye-Hand Movements

2021

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Significant progress has been made in understanding the computational and neural mechanisms that mediate eye and hand movements made in isolation. However, less is known about the mechanisms that control these movements when they are coordinated. Here, we outline our computational approaches using accumulation-to-threshold and race-to-threshold models to elucidate the mechanisms that initiate and inhibit these movements. We suggest that, depending on the behavioral context, the initiation and inhibition of coordinated eye-hand movements can operate in two modes—coupled and decoupled. The coupled mode operates when the task context requires a tight coupling between the effectors; a common command initiates both effectors, and a unitary inhibitory process is responsible for stopping them. Conversely, the decoupled mode operates when the task context demands weaker coupling between the effectors; separate commands initiate the eye and hand, and separate inhibitory processes are responsible for stopping them. We hypothesize that the higher-order control processes assess the behavioral context and choose the most appropriate mode. This computational mechanism can explain the heterogeneous results observed across many studies that have investigated the control of coordinated eye-hand movements and may also serve as a general framework to understand the control of complex multi-effector movements.

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“…This tight spatial and temporal coupling of the eye and hand movement is the hallmark of coordination [3]. However, despite this, distinct neural pathways are thought to control the initiation and stopping of these effectors [4,5]. The neural pathways involved in generating eye and hand movements are thought to diverge in the parietal cortex after common early processing in visual areas.…”

Section: Introductionmentioning

confidence: 99%

Computational Architecture Mediating Inhibitory Control of Coordinated Eye-Hand Movements

Jana¹,

Gopal²,

Murthy³

2021

Preprint

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Significant progress has been made in understanding the computational and neural architecture that mediates eye and hand movements made in isolation. However, less is known about the mechanisms that control these movements when they are coordinated. Here, we outline our computational approaches using accumulation-to-threshold and race-to-threshold models to elucidate the mechanisms that initiate and inhibit these movements. We suggest that, depending on the behavioral context, the initiation and inhibition of coordinated eye-hand movements can operate in two modes- coupled and decoupled. The coupled-mode operates when the task context requires a tight coupling between the effectors; a common command initiates both effectors, and a unitary inhibitory process is responsible for stopping them. Conversely, the decoupled mode operates when the task context demands weaker coupling between the effectors; separate commands initiate the eye and hand, and separate inhibitory processes are responsible for stopping them. We hypothesize that higher-order control processes assess the behavioral context and choose the most appropriate mode. This computational architecture can explain heterogeneous results observed across many studies that have investigated the control of coordinated eye-hand movements and may also serve as a general framework to understand the control of complex multi-effector movements.

show abstract

Functional Use of Eye Movements for an Acting System

Cited by 56 publications

References 103 publications

Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: A preliminary study

Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: A preliminary study

Computational Mechanisms Mediating Inhibitory Control of Coordinated Eye-Hand Movements

Computational Architecture Mediating Inhibitory Control of Coordinated Eye-Hand Movements

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